AbilityaiAbilityai/cornelius/.claude/skills/coherence-sweep/SKILL.md

coherence-sweep

Skill109 starsChanged 38 days agoMITView on GitHub

Run a full coherence sweep across the Brain Dependency Graph - computes staleness, lifecycle transitions, structural health, and generates a report

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The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.

≈0
Common · estimate
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≈4
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0
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Common
Distinctive
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Distinctive:
Run a full coherence analysis of the knowledge base using the Brain Dependency Graph engine.
line 12
Distinctive:
If not bootstrapped, run bootstrap first:
line 36
Distinctive:
Default (7-day lookback, lifecycle included, no tensions):
line 43
Distinctive:
Read the generated report and present key findings to the user:
line 62

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Files

SKILL.md

Brain Coherence Sweep

Run a full coherence analysis of the knowledge base using the Brain Dependency Graph engine. Identifies stale notes, lifecycle transitions, structural issues, and optionally productive tensions.

State Dependencies

Source	Location	Read	Write	Description
LBS Graph	`resources/local-brain-search/data/brain_graph.pkl`	✓		NetworkX graph
Enrichments	`resources/brain-graph/data/graph_enrichments.json`	✓	✓	Node/edge enrichments
Reports	`resources/brain-graph/reports/`		✓	Generated reports

Prerequisites

Brain Dependency Graph must be bootstrapped (run_brain_graph.sh bootstrap)
Local Brain Search index must exist

Process

Step 1: Check bootstrap status

cd $PROJECT_ROOT/resources/brain-graph
../local-brain-search/venv/bin/python cli.py status

If not bootstrapped, run bootstrap first:

../local-brain-search/venv/bin/python cli.py bootstrap

Step 2: Run coherence sweep

Default (7-day lookback, lifecycle included, no tensions):

../local-brain-search/venv/bin/python cli.py coherence

With options:

# Include tension detection (slower)
../local-brain-search/venv/bin/python cli.py coherence --tensions

# Custom lookback period
../local-brain-search/venv/bin/python cli.py coherence --days 14

# JSON output
../local-brain-search/venv/bin/python cli.py coherence --json

Step 3: Present results

Read the generated report and present key findings to the user:

Staleness alerts - Notes that need review due to upstream changes
Lifecycle transitions - Notes crossing phase boundaries (reflective -> crystallizing -> generative)
Structural health - Orphans, overloaded hubs, missing MOCs
Tensions (if enabled) - Productive contradictions for synthesis

Report is saved to: resources/brain-graph/reports/coherence-report-YYYY-MM-DD.md

Output Format

Present a concise summary with:

Count of stale notes with top 5 most affected
Notable lifecycle transitions (especially new generative notes)
Structural issues requiring attention
Path to full report

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